Correlated surface-charging behaviors of two electrodes in an electrochemical cell.

It is revealed herein that surface-charging behaviors of the two electrodes constituting an electrochemical cell cannot be described independently by their respective electric double-layer (EDL) properties. Instead, they are correlated in such a way that the surface-charging behavior of each electrode is determined by the EDL and the reaction kinetics at both electrodes. Two fundamental equations describing the correlated surface-charging behaviors are derived, and approximate analytical solutions are obtained at low and high current densities, respectively, to facilitate transparent understanding. Important implications of the presented conceptual analysis for theoretical and computational electrochemistry are discussed. A strategy of modulating the activity of one electrode by tuning EDL parameters of the other in a two-electrode electrochemical cell is demonstrated.

Hierarchical Modeling of the Local Reaction Environment in Electrocatalysis.

ConspectusElectrocatalytic reactions, such as oxygen reduction/evolution reactions and CO2 reduction reaction that are pivotal for the energy transition, are multistep processes that occur in a nanoscale electric double layer (EDL) at a solid-liquid interface. Conventional analyses based on the Sabatier principle, using binding energies or effective electronic structure properties such as the d-band center as descriptors, are able to grasp overall trends in catalytic activity in specific groups of catalysts. However, thermodynamic approaches often fail to account for electrolyte effects that arise in the EDL, including pH, cation, and anion effects. These effects exert strong impacts on electrocatalytic reactions. There is growing consensus that the local reaction environment (LRE) prevailing in the EDL is the key to deciphering these complex and hitherto perplexing electrolyte effects. Increasing attention is thus paid to designing electrolyte properties, positioning the LRE at center stage. To this end, unraveling the LRE is becoming essential for designing electrocatalysts with specifically tailored properties, which could enable much needed breakthroughs in electrochemical energy science.Theory and modeling are getting more and more important and powerful in addressing this multifaceted problem that involves physical phenomena at different scales and interacting in a multidimensional parametric space. Theoretical models developed for this purpose should treat intrinsic multistep kinetics of electrocatalytic reactions, EDL effects from subnm scale to the scale of 10 nm, and mass transport phenomena bridging scales from <0.1 to 100 µm. Given the diverse physical phenomena and scales involved, it is evident that the challenge at hand surpasses the capabilities of any single theoretical or computational approach.In this Account, we present a hierarchical theoretical framework to address the above challenge. It seamlessly integrates several modules: (i) microkinetic modeling that accounts for various reaction pathways; (ii) an LRE model that describes the interfacial region extending from the nanometric EDL continuously to the solution bulk; (iii) first-principles calculations that provide parameters, e.g., adsorption energies, activation barriers and EDL parameters. The microkinetic model considers all elementary steps without designating an a priori rate-determining step. The kinetics of these elementary steps are expressed in terms of local concentrations, potential and electric field that are codetermined by EDL charging and mass transport in the LRE model. Vital insights on electrode kinetic phenomena, i.e., potential-dependent Tafel slopes, cation effects, and pH effects, obtained from this hierarchical framework are then reviewed. Finally, an outlook on further improvement of the model framework is presented, in view of recent developments in first-principles based simulation of electrocatalysis, observations of dynamic reconstruction of catalysts, and machine-learning assisted computational simulations.

Pure Water Splitting Driven by Overlapping Electric Double Layers.

In pursuit of a sustainable future powered by renewable energy, hydrogen production through water splitting should achieve high energy efficiency with economical materials. Here, we present a nanofluidic electrolyzer that leverages overlapping cathode and anode electric double layers (EDLs) to drive the splitting of pure water. Convective flow is introduced between the nanogap electrodes to suppress the crossover of generated gases. The strong electric field within the overlapping EDLs enhances ion migration and facilitates the dissociation of water molecules. Acidic and basic environments, which are created in situ at the cathode and anode, respectively, enable the use of nonprecious metal catalysts. All these merits allow the reactor to exhibit a current density of 2.8 A·cm-2 at 1.7 V with a nickel anode. This paves the way toward a new type of water electrolyzer that needs no membrane, no supporting electrolyte, and no precious metal catalysts.

Deep learning-enhanced characterization of bubble dynamics in proton exchange membrane water electrolyzers.

The ever-increasing utility of imaging technology in proton exchange membrane water electrolyzer research raises the demand for rapid and precise image analysis. In particular, for optical video recordings, the challenge primarily lies in the large number of frames that impede the delineation of bubble dynamics with standard methods. In order to address this problem, the present study supports the automation of data analysis to facilitate swift, comprehensive, and measurable insights from captured imagery. We present a deep learning-based framework to perform high-throughput analyses of bubble dynamics using optical images of proton exchange membrane water electrolyzers. Leveraging a relatively small annotated imaging dataset of just 35 images, various configurations of the U-Net architecture were trained to perform bubble segmentation tasks. The best model achieved a precision of 95%, a recall of 78%, and an F1-score of 86% on the validation set. Subsequent to segmentation, the methodology enabled the rapid extraction of parameters such as time-resolved bubble area, size distributions, bubble position probability density, and individual bubble shape analytics. The findings underscore the potential of deep learning to enhance the analysis of polymer electrolyte membrane water electrolyzer imaging, offering a path toward more efficient and informative evaluations in electrochemical research.

Understanding the infrared spectrum of the protic ionic liquid [DEMA][TfO] by atomistic simulations.

Polymer-electrolyte fuel cells operating at a temperature above 100 °C would markedly reduce issues associated with water management in the cell and allow for a simplified system design. Available electrolytes such as fluoropolymers grafted with sulfonic acid groups or phosphoric acid either rely on the presence of water or they suffer from sluggish kinetics of the oxygen reduction reaction. Here, with experiments and atomistic simulations, we analysed vibrational spectra of the protic ionic liquid diethylmethylammonium triflate ([DEMA][TfO]) as an alternative electrolyte, with the aim to understand the statistical distribution of cations and anions in the electrolyte and the interaction of the H-bond with the surroundings. We present a comprehensive analysis of the infrared (IR) spectrum of [DEMA][TfO]. Special attention is given to understanding the high-frequency modes above 2500 cm-1, which exhibit a double peak feature in the experiment. While this feature can generally be attributed to the N-H vibrations of the cation, the precise mechanism behind the double peak was unclear. In this manuscript we managed to explain the nature of the double distribution, being influenced by different orientations between the DEMAs and TFOs. The correct assignment of observed vibrational modes is enabled by simulations of the ionic liquid as an infinitely extended fluid.

Dynamic Response of Ion Transport in Nanoconfined Electrolytes.

Ion transport in nanoconfined electrolytes exhibits nonlinear effects caused by large driving forces and pronounced boundary effects. An improved understanding of these impacts is urgently needed to guide the design of key components of the electrochemical energy systems. Herein, we employ a nonlinear Poisson-Nernst-Planck theory to describe ion transport in nanoconfined electrolytes coupled with two sets of boundary conditions to mimic different cell configurations in experiments. A peculiar nonmonotonic charging behavior is discovered when the electrolyte is placed between a blocking electrode and an electrolyte reservoir, while normal monotonic behaviors are seen when the electrolyte is placed between two blocking electrodes. We reveal that impedance shapes depend on the definition of surface charge and the electrode potential. Particularly, an additional arc can emerge in the intermediate-frequency range at potentials away from the potential of zero charge. The obtained insights are instrumental to experimental characterization of ion transport in nanoconfined electrolytes.

Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments.

Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally benign, and affordable is amongst the most pressing challenges for future socio-economic development. To that goal, hydrogen is presumed to be the most promising energy carrier. Electrocatalytic water splitting, if driven by green electricity, would provide hydrogen with minimal CO2 footprint. The viability of water electrolysis still hinges on the availability of durable earth-abundant electrocatalyst materials and the overall process efficiency. This review spans from the fundamentals of electrocatalytically initiated water splitting to the very latest scientific findings from university and institutional research, also covering specifications and special features of the current industrial processes and those processes currently being tested in large-scale applications. Recently developed strategies are described for the optimisation and discovery of active and durable materials for electrodes that ever-increasingly harness first-principles calculations and machine learning. In addition, a technoeconomic analysis of water electrolysis is included that allows an assessment of the extent to which a large-scale implementation of water splitting can help to combat climate change. This review article is intended to cross-pollinate and strengthen efforts from fundamental understanding to technical implementation and to improve the 'junctions' between the field's physical chemists, materials scientists and engineers, as well as stimulate much-needed exchange among these groups on challenges encountered in the different domains.

Asymmetric double-layer charging in a cylindrical nanopore under closed confinement.

This article presents a physical-mathematical treatment and numerical simulations of electric double layer charging in a closed, finite, and cylindrical nanopore of circular cross section, embedded in a polymeric host with charged walls and sealed at both ends by metal electrodes under an external voltage bias. Modified Poisson-Nernst-Planck equations were used to account for finite ion sizes, subject to an electroneutrality condition. The time evolution of the formation and relaxation of the double layers was explored. Moreover, equilibrium ion distributions and differential capacitance curves were investigated as functions of the pore surface charge density, electrolyte concentration, ion sizes, and pore size. Asymmetric properties of the differential capacitance curves reveal that the structure of the double layer near each electrode is controlled by the charge concentration along the pore surface and by charge asymmetry in the electrolyte. These results carry implications for accurately simulating cylindrical capacitors and electroactuators.

Virtual Materials Intelligence for Design and Discovery of Advanced Electrocatalysts.

Similar to advancements gained from big data in genomics, security, internet of things, and e-commerce, the materials workflow could be made more efficient and prolific through advances in streamlining data sources, autonomous materials synthesis, rapid characterization, big data analytics, and self-learning algorithms. In electrochemical materials science, data sets are large, unstructured/heterogeneous, and difficult to process and analyze from a single data channel or platform. Computer-aided materials design together with advances in data mining, machine learning, and predictive analytics are expected to provide inexpensive and accelerated pathways towards tailor-made functionally optimized energy materials. Fundamental research in the field of electrochemical energy materials focuses primarily on complex interfacial phenomena and kinetic electrocatalytic processes. This perspective article critically assesses AI-driven modeling and computational approaches that are currently applied to those objects. An application-driven materials intelligence platform is introduced, and its functionalities are scrutinized considering the development of electrocatalyst materials for CO2 conversion as a use case.

Unifying theoretical framework for deciphering the oxygen reduction reaction on platinum.

Rapid conversion of oxygen into water is crucial to the operation of polymer electrolyte fuel cells and other emerging electrochemical energy technologies. Chemisorbed oxygen species play double-edged roles in this reaction, acting as vital intermediates on one hand and site-blockers on the other. Any attempt to decipher the oxygen reduction reaction (ORR) must first relate the formation of oxygen intermediates to basic electronic and electrostatic properties of the catalytic surface, and then link it to parameters of catalyst activity. An approach that accomplishes this feat will be of great utility for catalyst materials development and predictive model formulation of electrode operation. Here, we present a theoretical framework for the multiple interrelated surface phenomena and processes involved, particularly, by incorporating the double-layer effects. It sheds light on the roles of oxygen intermediates and gives out the Tafel slope and exchange current density as continuous functions of electrode potential. Moreover, it develops the concept of a rate determining term, which should replace the concept of a rate determining step for multielectron reactions, and offers a new perspective on the volcano relation of the ORR.

Double layer of platinum electrodes: Non-monotonic surface charging phenomena and negative double layer capacitance.

In this study, a refined double layer model of platinum electrodes accounting for chemisorbed oxygen species, oriented interfacial water molecules, and ion size effects in solution is presented. It results in a non-monotonic surface charging relation and a peculiar capacitance vs. potential curve with a maximum and possibly negative values in the potential regime of oxide-formation.

Surface configuration and wettability of nickel(oxy)hydroxides: a first-principles investigation.

This article explores the wetting behavior of ß-type nickel hydroxide, ß-Ni(OH)2, and nickel oxyhydroxide, ß-NiOOH, by means of first-principles calculations. Water is found to interact weakly with ß-Ni(OH)2(001), but strongly with ß-NiOOH(001). As unveiled with the use of ab initio molecular dynamics simulations, surface water layers at ß-NiOOH(001) show a high degree of ordering correlated with a large surface polarization effect. In comparison, interfacial water at ß-Ni(OH)2(001) exhibits enhanced disorder and higher mobility. The weak interaction of water with ß-Ni(OH)2(001) is consistent with the small dipole moment of this surface. On the surface of ß-NiOOH(001), in addition to the significantly increased surface dipole moment, unsaturated O atoms increase the number of hydrogen bonds between water molecules and the surface, resulting in strong water binding. The wettability trends found in this simulation study are consistent with experimental observations. Another theoretical observation is the increased work function of ß-NiOOH(001) relative to ß-Ni(OH)2(001) that agrees with experimental results reported in the literature.

Modelling oxide formation and growth on platinum.

We present a mathematical model of oxide formation and growth on platinum. The motivation stems from the necessity to understand platinum dissolution in the cathode catalyst layer of polymer electrolyte fuel cells. As is known, platinum oxide formation and reduction are strongly linked to platinum dissolution processes. However, a consistent model of the oxidation processes on platinum does not exist. Our oxide growth model links interfacial exchange processes between platinum and oxygen ions with the transport of oxygen ion vacancies via diffusion and migration. A parametric analysis is performed to rationalize vital trends in oxide growth kinetics. The rate determining step of oxide formation and growth is identified as the extraction of platinum atoms at the metal-oxide interface. A kinetic effect is observed while adjusting the potential when growing the oxide layer, and the solution indicates that a structural change occurs at high potentials, around 1.5 VRHE. The model compares well to experimental data for various materials from various sources.

Theory of electrostatic phenomena in water-filled Pt nanopores.

The emerging field of nanoprotonics is concerned with controlling proton distribution and transport in nanoporous media. These phenomena, dictated by the surface charging properties of the host medium, are of vital importance in porous electrodes for fuel cells, electrolysers, supercapacitors and nanofluidic devices. In this theoretical study, we explore the interplay of the metal charging relation with the proton density and oxygen reduction activity in a water-filled nanopore with walls made of platinum. We exploit a non-monotonic charging behavior derived from a refined structural model of the Pt-solution interface. This charging relation replaces the oversimplified linear relation that has been widely used in practical applications. The water-filled pore, with one opening interfacing with a polymer electrolyte membrane as a proton source, always possesses negative surface charge in the potential range of 0-1.0 V (RHE). Therefore, its proton conductivity can be several orders higher than that of pure water. We obtain an analytical expression for the oxygen reduction activity of the nanopore and parameterize it using the polarization data of an ionomer-free thin-film Pt electrode. The structure vs. performance relation of the water-filled Pt nanopore is examined.

Magnetic susceptibility as a direct measure of oxidation state in LiFePO4 batteries and cyclic water gas shift reactors.

The possibility of correlating the magnetic susceptibility to the oxidation state of the porous active mass in a chemical or electrochemical reactor was analyzed. The magnetic permeability was calculated using a hierarchical model of the reactor. This model was applied to two practical examples: LiFePO4 batteries, in which the oxidation state corresponds with the state-of-charge, and cyclic water gas shift reactors, in which the oxidation state corresponds to the depletion of the catalyst. In LiFePO4 batteries phase separation of the lithiated and delithiated phases in the LiFePO4 particles in the positive electrode gives rise to a hysteresis effect, i.e. the magnetic permeability depends on the history of the electrode. During fast charge or discharge, non-uniform lithium distributionin the electrode decreases the hysteresis effect. However, the overall sensitivity of the magnetic response to the state-of-charge lies in the range of 0.03%, which makes practical measurement challenging. In cyclic water gas shift reactors, the sensitivity is 4 orders of magnitude higher and without phase separation, no hysteresis occurs. This shows that the method is suitable for such reactors, in which large changes of the magnetic permeability of the active material occurs.

Modeling the local potential at Pt nanoparticles in polymer electrolyte membranes.

We present a physical-analytical model for the potential distribution at Pt nanodeposits in a polymer electrolyte membrane (PEM). Experimental studies have shown that solid deposits of Pt in PEM play a dual role in radical-initiated membrane degradation. Surface reactions at Pt particles could facilitate the formation as well as the scavenging of ionomer-attacking radical species. The net radical balance depends on local equilibrium conditions at Pt nanodeposits in the PEM, specifically, their equivalent local electrode potential. Our approach utilizes a continuum description of crossover fluxes of reactant gases, coupled with the kinetics of electrochemical surface reactions at Pt nanodeposits to calculate the potential distribution. The local potential is a function of the PEM structure and composition, which is determined by PEM thickness, concentrations of H2 and O2, as well as the size and density distribution of Pt particles. Model results compare well with experimental data for the potential distribution in PEMs.

Water balance model for polymer electrolyte fuel cells with ultrathin catalyst layers.

We present a water balance model of membrane electrode assemblies (MEAs) with ultrathin catalyst layers (UTCLs). The model treats the catalyst layers in an interface approximation and the gas diffusion layers as linear transmission lines of water fluxes. It relates current density, pressure distribution, and water fluxes in the different functional layers of the assembly. The optimal mode of operation of UTCLs is in a fully flooded state. The main challenge for MEAs with UTCLs is efficient liquid water removal, to avoid flooding of the gas diffusion layers. The model provides strategies for increasing the critical current density for the onset of flooding, via liquid permeabilities, vaporization areas, and gas pressure differentials. Finally, we discuss methods to identify regimes of transport via water flux measurements.

Ab initio metadynamics study on hydronium ion dynamics at acid-functionalized interfaces: effect of surface group density.

This article presents an ab initio metadynamics study of elementary hydronium ion transitions at dense arrays of surface groups with sulfonic acid head groups. Calculations simulate minimally hydrated conditions of the interfacial ionic system. The specific focus is on the influence of the surface group density on hydronium ion transport. Results reveal a high sensitivity of the activation free energy of hydronium translocations to the surface group density. A spontaneous concerted transition with low activation barrier is found at a surface group separation of 6.8 Å. When hydroniums translocate concertedly, the activation barrier of the transition drops by more than a factor of two to the value of 0.25 eV. An approach is presented to determine interaction constants of hydronium ions and anionic surface groups as well as the surface group flexibility from the analysis of frequency spectra. These properties are discussed in the context of a recently developed soliton theory of interfacial proton transport.

Theoretical analysis of electrochemical surface-area loss in supported nanoparticle catalysts.

In polymer electrolyte fuel cells a decrease in catalytic surface-area within the cathode catalyst layer is a critical barrier to commercialization. This loss in catalytic surface-area manifests as a loss in cell voltage and thus power density of the cell. It has been established that potential cycling accelerates the loss in catalytic surface-area yet isolating the contributing mechanisms as well as relating mechanisms to operating conditions is not as straightforward. We approach the issue of surface-area loss deconvolution with a combined experimental, modelling and theoretical framework. The methodology is based on the Lifshitz-Slyozov-Wagner and Smoluchowski theories of particle size distribution evolution. Electrochemical surface-area loss experiments probing upper potential limits of 0.9 and 1.2 V as well as temperatures from 298 to 343 K were analyzed with the model. A dissolution and redeposition mechanism was correlated with the measurements for both upper potential limits; however, at the upper potential limit of 1.2 V, ambiguity between the coagulation and the dissolution and redeposition mechanisms was found. Notwithstanding, the extracted dissolution and redeposition parameters aligned with independent studies on Pt dissolution whereas similar positive comparisons with independent results were unable to be made for the coagulation mechanism.

Incorporating Electrolyte Correlation Effects into Variational Models of Electrochemical Interfaces.

We propose a way for obtaining a classical free energy density functional for electrolytes based on a first-principle many-body partition function. Via a one-loop expansion, we include coulombic correlations beyond the conventional mean-field approximation. To examine electrochemical interfaces, we integrate the electrolyte free energy functional into a hybrid quantum-classical model. This scheme self-consistently couples electronic, ionic, and solvent degrees of freedom and incorporates electrolyte correlation effects. The derived free energy functional causes a correlation-induced enhancement in interfacial counterion density and leads to an overall increase in capacitance. This effect is partially compensated by a reduction of the dielectric permittivity of interfacial water. At larger surface charge densities, ion crowding at the interface stifles these correlation effects. While scientifically intriguing already at planar interfaces, we anticipate these correlation effects to play an essential role for electrolytes in nanoconfinement.